Attempting to increase revenue requires ecommerce managers and marketers to pay close attention to three key KPIs. Namely, conversion rate (CR), average order value (AOV) and revenue per visitor (RPV).
Although each of these KPIs is important, none should be measured in isolation. Doing so often leads to unwanted blind spots; situations where an increase in one metric is accompanied by a decrease in another, leading to an overall decrease in revenue.
That’s what makes RPV great, it merges both CR and AOV into one measurable metric without leaving any blind spots (i.e. RPV = AOV * CR).
While all ecommerce businesses need to drive revenue, only newly established retailers (i.e. those with no revenue or customers) should put 100% of their time and effort into traffic acquisition as a means of driving revenue.
However, after initial traction (i.e. after the first million in sales), marginal returns from an acquisition-only strategy diminish. Once passed the one million in revenue line, more work is required to achieve the same results.
Unfortunately, most established ecommerce marketers today focus all of their energy and budgets on increasing traffic, when it would make much more sense to increase AOV, CR and retention.
Once visitors are acquired and transactions begin to roll in, increasing revenue should include two additional dimensions: converting more visitors into paying customers (CR) and increasing customer spend per conversion (AOV).
Driving traffic to a website costs money, but finding ways to increase AOV and CR generally does not (or costs very little comparatively). And since there is a cost associated with each order, increasing AOV is a direct way to gain revenue at little extra cost.
The problem with an acquisition focused marketing strategy
There are several problems with focusing all marketing efforts and budget on traffic acquisition. And this problem is amplified the longer the company has been in business.
Simply put, if visitors don’t convert, basket size doesn’t grow over time and customers don’t return, then a great deal of acquisition spend is wasted.
Worse yet, there is an opportunity cost since converting a greater proportion of visitors into customers, up-selling customers and retaining loyal customers are often more efficient and effective methods of driving revenue.
In this situation, the pursuit of bigger market share is akin to filling a leaky bucket with water. Since some customer churn is inevitable, companies looking to maintain their market share need to be at least as good at acquiring customers as they are bad at losing them.
But to grow market share, they must be either super-human at acquisition or exceptional at retention. The best strategy existing somewhere in the middle – combining traffic acquisition with conversion rate optimisation, cross-selling/up-selling and customer loyalty.
While there are numerous proven ways of increasing CR and AOV, including product recommendations, shipping and return policies, point-of-sale promotions and limited time offers, package and volume deals, better user experience (UX) and category navigation, marketing automation and retargeting, checkout optimisation and site speed, the vast majority of ecommerce businesses miss the opportunity to drastically improve CR and AOV with more relevant site-search.
Why site-search is often neglected
1. Most ecommerce retailers don’t know how poor their site-search is.
A good rule of thumb to judge if your site-search needs improvement is if the exit rate on search result pages is close to or on par with your website’s average bounce rate. Your search result pages should have some of the lowest exit rates on your site, since those searching have intent and often only exit search pages if results are irrelevant or no results were actually presented.
Another measure is your null-result rate (i.e. the percentage of total searches executed that return zero results). If that rate is above 5%, there is likely room for improvement.
2. Most ecommerce retailers don’t appreciate the criticality of site-search, especially on mobile.
Site-search is a critical customer touchpoint – an average of 30% of consumers use on-site search, but only 50% find what they’re looking for (Econsultancy).
Visitors who buy are 91% more likely to use site-search than those merely browsing (Findwise).
4 out of 5 smartphone users use retailer apps. With 47% of them using retailer apps for product search (ComScore).
Users with successful site searches are nearly twice as likely to convert compared to those who don’t search – since they are shopping with specific intent (Econsultancy).
3. Most ecommerce retailers believe they’ve done all they can to improve their site-search.
It’s incredible common to hear ecommerce managers and marketers say “our text-matching search should find a match because we regularly tag all our products with synonyms and keywords” or “we know what’s most important to our customers, so we sort our results according to what we know are top selling items” or “pushing high margin and sale items in search works fine, we see a lift when we manually insert our business logic into search”.
There are several problems with those statements. First, there are infinite ways and words your customers may use to describe your products. It’s impossible, and arrogant, to assume one person or team can anticipate and tag all of them. And tagging products with synonyms rarely takes into account pluralizations and misspellings.
Secondly, are your top selling items top selling because they’re what visitors actually wish to buy or because you constantly push them to the top of results?
And lastly, is pushing high margin or sale items really in the best interest of your customers? Wouldn’t it make more sense to try and help visitors find what they’re looking for first, before pushing your business agenda? Maybe your agendas overlap, but you’ll never know if you continue to manually manipulate a process that should be guided by consumer intent and relevance.
Why site-search should be a key part of any CRO plan
Improving ecommerce site-search is one of the most direct ways of increasing CR and AOV.
Basically, visitors who search have purchase intent and know what they want. Not giving them accurate and relevant search results not only leads to a poor customer experience, it almost always means lost sales.
On the other hand, having highly relevant search that actually attempts to capture customer intent can lead to conversion rate and revenue growth unmatched by most other CR initiatives.
We’re talking top-line revenue growth of 10-20%, search conversion rate growth (i.e. conversion rate among visitors who search) of 30-50%, AOV growth of 75% and search page exit rate reductions of 70%.
Here’s just one of many examples:
Another one of our customers – Kontorsmagasinet – did an extensive of A/B test to measure the CR and AOV impact of having more relevant site-search. After a 35 day 50/50 split test, Kontorsmagasinet realised the follow results:
Where to begin and how to improve your site-search?
● Find out how much your site-search is used to today and how those particular visitors behave. Look into how much revenue stems directly from visitors who search and what your current search conversion rate is.
You can use Google Analytics (Content > Site Search > Usage) to know whether or not users are actively using product search and how they convert.
You will notice that visitors who site-search often convert at twice the rate or more compared to visitors without site- search.
● Design a more appealing search box: One of the possible reasons your visitors may not be using your product search is the placement of your search bar. It used to be that having a limited catalogue justified having poor site-search (i.e. people would just browse), but growth in mobile shopping kills this argument (have you ever browsed hundreds of products on a mobile phone? Not fun).
● Test your search for accuracy: search for words (singular, plural, misspelled) and see if the same results appear. For example, if you’re in sporting goods, a search for ‘basketball’, ‘basketballs’ and ‘bascetblls’ should all return the same results.
● Test your search for relevancy: search for a popular product type term and see if other similar products also come up. For example, if you’re a grocery retailer, a search for ‘cookie’ should also yield products described as biscuits, wafers and Oreos.
● Offer a list of related results to drive product discovery: consider presenting a secondary list of results that are “related” to the products that come up as direct search results. A sort of “you might also like” list.
For example, if you’re a grocery retailer, a search for ‘Red Bull’ should trigger a side list of results that includes other types of energy drinks and products; a search for ‘lemon’ should bring up a list of other citrus fruit like limes and grapefruit.
● Use behavioural data to refine search results ranking: great search should learn and get better over-time. Use actual visitor clicks, add-to-baskets and purchases to refine what results are most relevant to a particularly query and should appear on top.
One downside to this feature is the cold start problem – it can take a significant amount of time to accumulate enough behavioural data to draw any conclusions.
● Continuously work to improve the quality and structure of your product data: Forrester research shows that 71% of online shoppers actively research product information online to help them make better purchase considerations.
Centralising and structuring product data using Product Information Systems (PIM) helps you ensure consistency of information across channels, scale your product assortment and support increasingly demanding channel distribution partners. And it also greatly improves site-search functionality.
At a minimum, great search requires your product meta-data to include: product identifier, title, description, image url, brand/make/supplier, product series name, category path (category 1, category 2, etc.), price and in-stock flag.
● Consider outsourcing site-search to a 3rd party: Building great search – beyond simple text-matching – is hard! Building and maintaining search in-house is time consuming and tedious; often requiring staffing your ecomm/dev team with 1-5 people solely dedicated to the issue of search. And relying on the default search functionality of your ecommerce platform is not the best solution either.
Search is not their core competency, and in most cases these ecommerce platforms prefer to hand this function over to a specialised 3rd party.
Finally, providing search that’s truly relevant and that learns from user behaviour requires building sophisticated algorithms. So if you aren’t keen on hiring in-house mathematicians, consider services like Loop54 instead.
Let’s quickly recap
● CR is derived by taking the number of transactions (orders) divided by the number of unique visitors (total transactions/unique visitors).
● CR growth is helpful because it costs more to acquire new customers than it does to convert more of your current visitors. Therefore, increasing CR gives you more revenue for the same acquisition cost.
● But, focusing solely on increasing CR can make business susceptible to a dangerous blind spot – when increasing CR is accompanied by decreasing AOV.
● AOV is measured by taking the total revenue divided by the number of unique transactions (total revenue/unique transactions).
● Comparing AOV against Cost Per Order gives a great idea of the profits made on each order.
● Ecommerce marketers often focus much of their energy on increasing traffic to a website, when it would make much more sense to increase their AOV. Driving traffic to a website costs money, but finding ways to increase AOV generally does not (or very little comparatively). Since there is a cost associated with each order, increasing AOV is a way to drive direct revenue at little extra cost, therefore increasing profits.
● RPV takes the AOV and multiplies it by the conversion rate (RPV = AOV x Conversion Rate).
● Since every ecommerce business needs to drive revenue, they will always start with attracting visitors. Once that is achieved, increasing revenue involves a two-pronged approach: Converting more visitors into paying customers (CR) and increasing customer spend per conversion (AOV). RPV involves both these dimensions without leaving any blind spots.
Why site-search matters to CR and AOV growth
● Site-search is a critical customer touchpoint – up to 30% of consumers use on-site search, but only 50% find what they’re looking for (Econsultancy).
● The frustration caused by irrelevant or null search results is amplified for the 48% of consumers who mobile shop – as screen real estate is limited and a desire to minimize keystrokes is paramount (PWC).
● Shoppers who had null-result site searches are three times more likely to leave (Wired).
● Those who buy are 91% more likely to use site-search than those merely browsing (Findwise).
● Users with successful site searches are nearly twice as likely to convert compared to those who don’t search – since they are shopping with intent (Econsultancy).
● Successful search experiences don’t just involve a type and click, they also facilitate a browse experience, often leading to higher AOV (Forrester, 2015)
● 42% of in-store shoppers search for information online while in-store – and 46% of them go to the retailer’s site or app to search for information (Google, Ipsos MediaCT Sterling Brands).
● Product searches don’t often start with Google Search Engine. 31% of shoppers will use the retailers own channels, with 13% going to the physical store, 14% to the retailer’s website and 4% going to retailer’s mobile app.
● 4 out of 5 smartphone users use retailer apps. With 47% of them using retailer apps for product search.
● Millennials leverage technology more than any other group. This group more likely to search for products on retailer’s mobile app and social media sites.
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